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Lookup NU author(s): Mohamed Mohamed, Professor Gary Montague, Professor Jarka Glassey
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 The Authors. This paper describes the implementation of inline near infrared spectroscopy measurements to determine the key quality attributes of caramel in an industrial manufacturing process. The current control strategy is based around offline sampling and laboratory analysis which is costly, time-consuming and compromises operational control. Moving to inline analysis overcomes these limitations but the development of robust calibration models is a challenging task. Product recipe changes and natural raw material variation compound the issues arising in typical calibration model development. It is demonstrated that with appropriate spectroscopic signal pre-treatment and pattern recognition algorithm analysis, it is possible to provide the operators with a robust assessment of the caramel key quality measures so that they can respond in a timely manner if further processing actions are required. Results demonstrate the ability for NIR measurement to detect batch deviations that subsequently were judged to fall outside of the quality control limits as determined in pre-release laboratory assessment.
Author(s): Mohamed MKE, Montague G, Glassey J, Morrow P, Ryan V, Dawson S
Publication type: Article
Publication status: Published
Journal: Journal of Food Engineering
Year: 2024
Volume: 361
Print publication date: 01/01/2024
Online publication date: 29/08/2023
Acceptance date: 28/08/2023
Date deposited: 18/09/2023
ISSN (print): 0260-8774
ISSN (electronic): 1873-5770
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.jfoodeng.2023.111717
DOI: 10.1016/j.jfoodeng.2023.111717
Data Access Statement: Data will be made available on request.
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